CN114784867A - Cooperative control method for improving stability of new energy accessed to weak current grid system - Google Patents

Cooperative control method for improving stability of new energy accessed to weak current grid system Download PDF

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CN114784867A
CN114784867A CN202210507037.8A CN202210507037A CN114784867A CN 114784867 A CN114784867 A CN 114784867A CN 202210507037 A CN202210507037 A CN 202210507037A CN 114784867 A CN114784867 A CN 114784867A
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power
renewable energy
distributed renewable
load
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姜晓锋
韩晓言
***
魏巍
陈刚
周波
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Electric Power Research Institute of State Grid Sichuan Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H02J3/241—The oscillation concerning frequency
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin

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Abstract

The invention discloses a cooperative control method for improving stability of a new energy access weak grid system, and relates to the field of stability of a grid system. The method comprises the following steps: a: the incremental cost of each distributed renewable energy source and the electricity utilization benefit of the flexible load are used as consistency state variables, and frequency deviation is obtained; b: calculating or updating the active output power of each distributed renewable energy source, the required power of each load and a consistency state variable; c: if the active output power exceeds the limit or the network merging and exiting phenomena occur, updating the network topology structure, recalculating the consistency state variable, otherwise, performing the step D; d: updating the current frequency deviation, if the frequency deviation is within the allowable error range, the current output power output configuration mode is reasonable, otherwise, performing the step E; e: and C, performing additional frequency modulation control, calculating a self-adaptive frequency correction coefficient, and returning to the step B. The invention can realize the cooperative control of the source-load two sides and ensure that the power distribution network system meets the global power stability.

Description

Cooperative control method for improving stability of new energy accessed to weak current grid system
Technical Field
The invention relates to the field of system stability under the condition of a weak power grid, in particular to a cooperative control method for improving the stability of a new energy source accessed to the weak power grid system.
Background
With the proposal of the national 'double-carbon' target, the construction of a novel power system containing high-proportion renewable energy becomes a main guide for development, and how to improve the stability of the power system when massive distributed renewable energy is connected to the grid becomes a key research problem. The distributed renewable energy source has the characteristics of high intermittence, randomness and fluctuation, and meanwhile, the novel load is continuously increased, so that the active power distribution network has source-load bidirectional uncertainty, and difficulty is brought to power stability and voltage stability.
The distributed control algorithm has the advantages that the distributed control algorithm can still effectively operate under the condition that communication is limited or unreliable, the privately owned data resources of all the dispatching centers can be reserved, and meanwhile, the distributed control algorithm also has the characteristics of high efficiency, plug and play and the like, wherein the consistency algorithm is an effective method for solving the distributed regulation and control problem under the weak power grid environment.
However, the consistency control aiming at the distributed power supplies at present essentially needs a centralized information station to integrate and process the information of each power supply, so that the algorithm cannot realize complete distribution, and cannot effectively ensure the power stability of the system during the source-load bidirectional change.
Therefore, it is necessary to provide a cooperative control method with additional frequency modulation control to improve the system stability of the new energy accessed to the weak power grid.
Disclosure of Invention
Aiming at the problems that complete distribution cannot be realized and the power stability of the system during bidirectional source-load change cannot be effectively guaranteed in the prior art, the invention provides a cooperative control method for improving the stability of a new energy access weak grid system, which aims to: the characteristics of randomness, volatility, intermittency and the like of the new energy power supply are considered, the fact that the power distribution network presents source-load bidirectional uncertainty is considered, a distributed control algorithm is combined with additional frequency modulation control, cooperative control of the source-load two sides is achieved, and the power distribution network system meets the requirement of global power stability.
The technical scheme adopted by the invention is as follows:
a cooperative control method for improving stability of a new energy access weak grid system comprises the following steps:
step A: the incremental cost of each distributed renewable energy source in the low-voltage distribution network and the electricity utilization benefit of a flexible load are used as consistency state variables, a Laplace matrix L and an adjacent matrix A are obtained according to a distribution network topological graph, and frequency deviation is obtained through a phase-locked loop link in a controller;
and B: calculating or updating the active output power of each distributed renewable energy source, the required power of each load and the consistency state variable;
step C: if the active output power of each distributed renewable energy source in the current step exceeds the power boundary limit or grid connection or grid disconnection occurs, updating a network topology structure, recalculating the Laplace matrix L and the adjacent matrix A, recalculating the consistency state variable, and otherwise, performing the step D;
step D: updating the current frequency deviation, if the frequency deviation meets the allowable error range, the output power of each current distributed renewable energy source is in a reasonable output configuration mode, otherwise, performing the step E;
and E, step E: and C, performing additional frequency modulation control, calculating a self-adaptive frequency correction coefficient, and returning to the step B.
Preferably, in the step a, the incremental cost of the distributed renewable energy source and the electricity utilization efficiency calculation formula of the flexible load are as follows:
Figure BDA0003636416200000021
Figure BDA0003636416200000022
in the formula, alphai、βi、γiConstant term, first order term coefficient and second order term coefficient of incremental cost function, aj、bj、cjRespectively a constant term, a first-order term coefficient and a second-order term coefficient of the power consumption benefit function, PGiOutput power, P, for renewable energy iDjIs the demanded power of the load j, CiTo incremental cost, BjThe electric energy is used.
Preferably, in step B, a specific method for calculating or updating the coherency state variable is as follows:
the consistency variable updating formula of the main power generation unit for generating power by renewable energy sources is as follows:
Figure BDA0003636416200000023
the consistency variable updating formula of the secondary power generation unit for generating power by renewable energy sources is as follows:
Figure BDA0003636416200000024
the consistency variable updating formula of the main load is as follows:
Figure BDA0003636416200000025
the consistency variable update formula from the load is:
Figure BDA0003636416200000031
wherein:
Figure BDA0003636416200000032
Δfi(k)＝f*-fi(k)
in the formula, λi(k) Is the consistency state variable of the ith distributed renewable energy source at the kth iteration, lambdaj(k) Is the consistency state variable of the jth flexible load at the kth iteration, aijFor the elements of ith row and jth column of network topology adjacency matrix A, H*(k) For the tuning term of the frequency modulation control, Ω is the adaptive global balance correction factor, Δ fi(k) Is the frequency offset value at the kth iteration. f. ofi(k) Frequency, f, measured for the kth iteration of a distributed renewable energy source equipped with a phase-locked loop*Is the nominal frequency of the system. Lambdat(k) And λj(k) Are not meant to be physically identical, but are not represented by the same subscripts on the same formula. In the above consistency variable update formula, the value of t is from 1 to n, which refers to the summation of all power consistency variables in the previous iteration, so two subscript loops are required in the programming, and two subscripts are required in the formula for representation.
Preferably, in the step C, if the active output power of each distributed renewable energy in the current step exceeds the maximum power limit, the distributed renewable energy operates according to the maximum constrained power, and the consistency state variable of the distributed renewable energy is updated; if the active output power of each distributed renewable energy source in the current step is smaller than the minimum power limit, the distributed renewable energy sources operate according to the minimum constraint power, and the consistency state variable of the distributed renewable energy sources is updated; and if grid connection or grid disconnection of the distributed renewable energy sources occurs, updating the network topological graph, recalculating the Laplace matrix L and the adjacency matrix A, and updating the consistency state variable.
Preferably, in step E, a specific method for adding frequency modulation control is as follows:
the additional frequency modulation control theory is as follows:
(1) for the distributed power supply of the conventional energy, the difference adjustment coefficient is as follows:
Figure BDA0003636416200000033
in the formula, KGRegulating power, Δ P, per unit for a distributed power supply of conventional energyGThe active power variation of distributed power supplies, which are conventional energy sources.
(2) For an active power distribution network and a flexible load containing distributed renewable energy sources, the difference adjustment coefficient participating in frequency modulation is as follows:
Figure BDA0003636416200000041
Figure BDA0003636416200000042
in the formula, KPVRegulating power, K, for a unit of distributed renewable energydRegulating power, Δ P, for a unit of loadPVActive power variation, Δ P, for distributed renewable energy sourcesdIs the active power variation of the load, fPVThe distributed renewable energy is participated in the response dead zone of frequency modulation control.
Thus, for the entire distribution network system, the unit regulated power is:
K＝(1-η)KG+ηKPV+Kd
Ks＝(1-η)KG+ηKPV
Figure BDA0003636416200000043
where η is the permeability of the distributed renewable energy within the cluster, KGRegulating power, K, for a unit of a distributed power supply of conventional energyPVRegulating power, K, for a distributed renewable energy sourcedAdjusting power for unit of load, delta f is frequency deviation in active distribution network cluster, delta P is sudden change of load on demand side, and KsRegulating power, K, for a distributed renewable energy sourcedFor unit regulation of flexible loads on demand sideAnd (4) saving power.
Preferably, in step E, the adaptive frequency correction coefficient is calculated by:
and E1, when the frequency deviation is larger than the frequency deviation critical value, the power supply side and the load side participate in frequency modulation at the same time, and the calculation formula of the self-adaptive frequency correction coefficient is as follows:
Ω＝εi(Ks+Kd)
in the formula, KsRegulating power, K, for a distributed renewable energy sourcedRegulating power, epsilon, for flexible loadsiThe convergence coefficient of the ith distributed renewable energy source in the power distribution network.
And E2, when the frequency deviation is smaller than the frequency deviation critical value, the power supply side participates in frequency modulation independently, and the calculation formula of the self-adaptive frequency correction coefficient is as follows:
Ω＝εiKs
in the formula, KsRegulating power, epsilon, for units of distributed renewable energyiConvergence factor, epsilon, for the ith distributed renewable energy within the distribution networkiThe value is 0.005.
Preferably, the allowable range of the frequency deviation is [ -0.2Hz,0.2Hz ] according to GB/T15945-.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
the invention adopts a cooperative control idea, combines a distributed control algorithm with an additional frequency modulation control module, realizes the overall power stability of the system while realizing the completely distributed regulation, gets rid of a centralized information processing mechanism in the traditional algorithm, and effectively solves the problem of the dynamic stability of the power system under the condition of source-load bidirectional uncertainty.
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The invention will now be described, by way of example, with reference to the accompanying drawings, in which:
fig. 1 is a flowchart of a control method of the present invention.
Fig. 2 is a communication topology diagram of an IEEE39 node system.
Fig. 3 is an iteration diagram of the consistency variable of the validity test of the invention.
Fig. 4 is a simulation diagram of active power output of each renewable energy source in the validity test of the invention.
FIG. 5 is a graph of the total power change on both sides of the "Source-load" test of the effectiveness of the present invention.
FIG. 6 is an iteration chart of the compliance variable of the compliance load fluctuation test of the present invention.
Fig. 7 is a graph of active power output change of each renewable energy source in the flexible load fluctuation test of the invention.
FIG. 8 is a diagram of the total power change on both sides of the flexible load fluctuation test "Source-load" according to the present invention.
FIG. 9 is an iterative graph of a power generation unit fluctuation test consistency variable of the present invention.
Fig. 10 is a graph of active power output variation of each renewable energy source in the fluctuation test of the power generation unit.
FIG. 11 is a diagram of the total power change on both sides of the power generation unit fluctuation test "Source-load".
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as presented in the figures, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
The present invention is described in detail below with reference to fig. 1 to 5.
As shown in fig. 1, the cooperative control method for improving the stability of a new energy access weak grid system specifically includes the following steps:
step A: the incremental cost of each distributed renewable energy source in the low-voltage distribution network and the electricity utilization benefit of the flexible load are used as consistency state variables, the Laplace matrix L and the adjacency matrix A are obtained according to a distribution network topological graph, and the frequency deviation is obtained through a phase-locked loop link in the controller.
Step A1: the incremental cost of the distributed renewable energy sources and the electricity utilization benefit calculation formula of the flexible load are as follows:
Figure BDA0003636416200000061
Figure BDA0003636416200000062
in the formula, alphai、βi、γiConstant term, first order term coefficient and second order term coefficient of incremental cost function, aj、bj、cjRespectively, constant term, first order term coefficient and second order term coefficient of the power consumption benefit function, PGiOutput power, P, for renewable energy iDjIs the demanded power of load j.
Step A2: the consistent variables of incremental cost and electricity usage benefit are extracted and defined as follows:
processing the distributed cooperative regulation and control model by using a Lagrange multiplier method, solving a partial derivative of the decision quantity and the Lagrange multiplier by using a KKT first-order optimality condition, and defining consistency variables of each power generation unit and each flexible load as follows under the condition of not considering inequality constraint:
a power generation unit: lambda [ alpha ]i＝βi+2γiPGi(k)
Flexible load: lambdaj＝bj+2cjPDj(k)
Step A3: the method comprises the following steps of obtaining a Laplace matrix L and an adjacency matrix A according to a network topological graph of the power distribution network, and specifically comprises the following steps:
using directed graph G tableA communication topology diagram of a distributed power distribution system under weak grid conditions is shown. If at least one path exists between any two different nodes in the graph, the graph is a connected graph. The topology of the graph can be represented by a symmetrical n-order adjacency square matrix A ═ aij)n×nAnd (4) showing. Wherein, the adjacent square matrix element aijCan be defined as:
Figure BDA0003636416200000071
in the formula: diIs the total number of nodes connected to node i (including i itself), DiA set of these nodes connected to node i.
In addition, a laplacian matrix L ═ (L) for a fully distributed power distribution system may be definedij)n×nWherein l isij＝-aij，
Figure BDA0003636416200000072
Step A4: and acquiring the frequency deviation through a phase-locked loop PLL link in a controller of each distributed power supply.
And B: and calculating or updating the active output power of each distributed power supply, the required power of each load and the consistency state variable.
Step B1: the specific method for calculating or updating the active output power of each distributed power supply and the required power of each load is as follows:
active output power of distributed power supply:
Figure BDA0003636416200000073
required power of load:
Figure BDA0003636416200000074
s22: the update formula for the coherency state variable is:
1) the consistency variable updating formula of the main power generation unit for generating power by renewable energy sources is as follows:
Figure BDA0003636416200000075
2) the consistency variable updating formula of the secondary power generation unit for generating power by renewable energy sources is as follows:
Figure BDA0003636416200000076
3) the consistency variable updating formula of the main load is as follows:
Figure BDA0003636416200000077
4) the consistency variable update formula from the load is:
Figure BDA0003636416200000081
wherein:
Figure BDA0003636416200000082
Δfi(k)＝f*-fi(k)
in the formula, λi(k) Is the consistency state variable, lambda, of the ith distributed renewable energy source at the kth iterationj(k) Is the consistency state variable of the jth flexible load at the kth iteration, aijFor the elements of ith row and jth column of network topology adjacency matrix A, H*(k) For the tuning term of the frequency modulation control, Ω is the adaptive global balance correction factor, Δ fi(k) Is the frequency offset value, f, at the kth iterationi(k) Frequency, f, measured for the kth iteration of a distributed renewable energy source equipped with a phase-locked loop*Is the nominal frequency of the system.
Step C: if the active output power of each distributed renewable energy source in the current step exceeds the maximum power limit, the distributed renewable energy sources are operated according to the maximum constraint power, and then the consistency state variable of the distributed renewable energy sources is updated; if the power of each distributed renewable energy source in the current step is smaller than the minimum power limit, the distributed renewable energy sources are operated according to the minimum constraint power, and then the consistency state variable of the distributed renewable energy sources is updated; and if grid connection or grid disconnection of the distributed renewable energy sources occurs, updating the network topological graph, recalculating the Laplace matrix L and the adjacency matrix A, and further updating the consistency state variable.
Step D: updating the current frequency deviation, if the frequency deviation satisfies the allowable error range, i.e. | fi(k)-f*If the absolute value is less than 0.2, the output power of each current distributed renewable energy source is a reasonable output configuration mode, otherwise, the step E is carried out.
And E, step E: and C, performing additional frequency modulation control, calculating a self-adaptive frequency correction coefficient, and returning to the step B.
The additional frequency modulation control theory is as follows:
(1) for the distributed power supply of the conventional energy, the difference adjustment coefficient is as follows:
Figure BDA0003636416200000083
in the formula, KGPower, Δ P, regulated for unity for distributed power of conventional energyGThe active power variation of a distributed power supply that is a conventional energy source.
(2) For an active power distribution network and a flexible load containing distributed renewable energy sources, the difference adjustment coefficient participating in frequency modulation is as follows:
Figure BDA0003636416200000091
Figure BDA0003636416200000092
in the formula, KPVAs distributed renewable energy sourcesUnit of regulated power, KdRegulating power, Δ P, for a unit of loadPVActive power variation, Δ P, for distributed renewable energy sourcesdIs the active power variation of the load, fPVAnd a response dead zone for the distributed renewable energy sources to participate in frequency modulation control.
Thus, for the entire distribution network system, the unit regulated power is:
K＝(1-η)KG+ηKPV+Kd
Ks＝(1-η)KG+ηKPV
Figure BDA0003636416200000093
where η is the permeability of the distributed renewable energy within the cluster, KGRegulating power, K, for a unit of a distributed power supply of conventional energyPVRegulating power, K, for a unit of distributed renewable energydAdjusting power for unit of load, delta f is frequency deviation in active distribution network cluster, delta P is sudden change of load on demand side, and KsRegulating power, K, for a unit of distributed renewable energydThe power is regulated for the unit of the demand side flexible load.
The calculation method of the self-adaptive correction coefficient comprises the following steps:
(1) when the frequency deviation is larger than the frequency deviation critical value, the power supply side and the load side participate in frequency modulation and repair simultaneously
The positive coefficient calculation formula is as follows:
Ω＝εi(Ks+Kd)
in the formula, KsRegulating power, K, for a unit of distributed renewable energydRegulating power, epsilon, for units of flexible load on demand sideiIs the convergence coefficient of the ith distributed renewable energy source in the cluster.
(2) When the frequency deviation is less than the critical value of the frequency deviation, the power supply side participates in the frequency modulation independently, and the correction coefficient meter
The calculation formula is as follows:
Ω＝εiKs
in the formula, KsRegulating power, epsilon, for a unit of distributed renewable energyiThe convergence factor for the ith distributed renewable energy source in the cluster.
Taking an IEEE-39 node 10-machine 19 load system as an example, fig. 2 is a communication topology diagram of an IEEE39 node system. Wherein, the communication nodes 1-10 represent the renewable energy power generation units G respectively1-G10The communication nodes 11-29 represent flexible loads 11-29, respectively. The system comprises 10 distributed renewable energy power generation units and 19 flexible loads, and the parameters of all the power generation units and the flexible loads are shown in table 1.
TABLE 110 machine 19 load System parameters
Figure BDA0003636416200000101
Figure BDA0003636416200000111
The following provides simulation calculations for verification of 3 scenarios:
(1) scene 1: the control method is verified to be capable of effectively maintaining the stability of the system through cooperative control.
During distributed control, renewable energy G1 is selected as a main power generation unit, the flexible load 11 is a main flexible load, the sampling step length is set to be 0.02s, and the convergence coefficient epsilon isi0.005 was taken. The simulation results are shown in fig. 3 to 5: FIG. 3 is an iterative graph of consistency variables showing the values of the consistency variables during the iteration; fig. 4 is a simulation diagram of active power output of each renewable energy source, which shows the magnitude of active power output by each renewable energy source power generation unit; fig. 5 is a graph of total power variation on both sides of the "source-load", which shows the magnitude of the source side output power and the load required power. From fig. 3, it can be known that all consistency variables in the system converge to the same optimal value and remain stable; fig. 4 shows that the active power output of each renewable energy source finally keeps stable; from fig. 5, it can be seen that the total supply and demand power of the system reaches the equilibrium state. Therefore, the temperature of the molten metal is controlled,the control method is effective in maintaining system stability.
(2) Scene 2: it is verified that the control method can cope with the fluctuation of the flexible load.
On the basis of the scenario 1, it is assumed that when t is 24s, the flexible load 29 exits the power grid operation; when t is 48s, the flexible load 29 is connected to the grid again for operation. The simulation results are shown in fig. 6 to 8, wherein fig. 6 is a consistency variable iteration graph showing the values of each consistency variable in the iteration process; fig. 7 is a graph showing a change in active power output of each renewable energy source, which shows the magnitude of active power output by each renewable energy source power generation unit; fig. 8 is a graph of total power variation on both sides of the "source-load", showing the magnitude of the source side output power and the load required power. According to the simulation result, when t is 24s, the flexible load 29 is off the network, the consistency variable is converged again to reach a new steady value, and the stability is kept; the active power output of each distributed renewable energy source is redistributed, and the total supply and demand power of the system reaches a new stable equilibrium state; and when t is 48s, the flexible load 29 is connected to the grid again, the consistency variable recovers the original steady state value, the active power output of each distributed renewable energy source recovers to the original output power value, and the supply and demand power recovers to the stable balanced state. Therefore, the control method can cope with the fluctuation of the flexible load.
(3) Scene 3: it is verified that the control method can cope with fluctuations in the power generation unit.
On the basis of scenario 1, it is assumed that when t is 24s, the power generation unit G2 exits the grid operation; when t is 48s, the power generation unit G2 is newly grid-connected. The simulation results are shown in fig. 9 to 11, wherein fig. 9 is a consistency variable iteration graph showing the values of each consistency variable in the iteration process; fig. 10 is a graph showing a change in active power output of each renewable energy source, which shows the magnitude of active power output by each renewable energy source power generation unit; fig. 11 is a graph of total power variation on both sides of the "source-load", which shows the magnitude of the source side output power and the load required power. According to the simulation result, when t is 24s, the power generation unit G2 quits the network, the consistency variable is converged again to reach a new steady state value, the active power output of each distributed renewable energy source is redistributed, and the supply and demand power of the system reaches a new steady state; and when t is 48s, the power generation unit G2 is connected to the grid again, the consistency variable recovers the original steady state value, the active power output of each distributed renewable energy source recovers to the original output power value, and the supply and demand power recovers to the stable balance state. Thus, the control method can cope with fluctuations in the power generation unit.
In conclusion, the characteristics of randomness, volatility, intermittence and the like of the new energy power supply are considered, the fact that the power distribution network presents 'source-load' bidirectional uncertainty is considered, and cooperative control of two sides of 'source-load' is achieved through additional frequency modulation control and a distributed algorithm, so that the power distribution network system meets the requirement of global power stability.
The above-mentioned embodiments only express the specific embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for those skilled in the art, without departing from the technical idea of the present application, several changes and modifications can be made, which are all within the protection scope of the present application.

Claims (7)

1. A cooperative control method for improving stability of a new energy access weak grid system is characterized by comprising the following steps:
step A: the incremental cost of each distributed renewable energy source in the low-voltage distribution network and the electricity utilization benefit of a flexible load are used as consistency state variables, a Laplace matrix L and an adjacent matrix A are obtained according to a distribution network topological graph, and frequency deviation is obtained through a phase-locked loop link in a controller;
and B, step B: calculating or updating the active output power of each distributed renewable energy source, the required power of each load and the consistency state variable;
and C: if the active output power of each distributed renewable energy source in the current step exceeds the power boundary limit or grid connection or grid disconnection occurs, updating a network topology structure, recalculating the Laplace matrix L and the adjacent matrix A, recalculating the consistency state variable, and otherwise, performing the step D;
step D: updating the current frequency deviation, if the frequency deviation meets the allowable error range, the output power of each current distributed renewable energy source is in a reasonable output configuration mode, otherwise, performing the step E;
and E, step E: and C, performing additional frequency modulation control, calculating a self-adaptive frequency correction coefficient, and returning to the step B.
2. The cooperative control method for improving the stability of the new energy accessed to the weak grid system according to claim 1, wherein in the step a, the incremental cost of the distributed renewable energy and the power utilization benefit calculation formula of the flexible load are as follows:
Figure FDA0003636416190000011
Figure FDA0003636416190000012
in the formula, alphai、βi、γiConstant term, first order term coefficient and second order term coefficient of incremental cost function, respectively, aj、bj、cjRespectively a constant term, a first-order term coefficient and a second-order term coefficient of the power consumption benefit function, PGiOutput power, P, for renewable energy iDjIs the demanded power of the load j, CiTo incremental cost, BjThe electric energy is used for electric benefits.
3. The cooperative control method for improving the stability of the new energy access weak grid system according to claim 1, wherein in the step B, the specific method for calculating or updating the consistency state variable is as follows:
the consistency variable updating formula of the main power generation unit for generating power by renewable energy sources is as follows:
Figure FDA0003636416190000013
the consistency variable updating formula of the secondary power generation unit for generating power by renewable energy sources is as follows:
Figure FDA0003636416190000014
the consistency variable updating formula of the main load is as follows:
Figure FDA0003636416190000021
the consistency variable update formula from load is:
Figure FDA0003636416190000022
wherein:
Figure FDA0003636416190000023
Δfi(k)＝f*-fi(k)，
in the formula, λi(k) Is the consistency state variable, lambda, of the ith distributed renewable energy source at the kth iterationj(k) A coherency state variable for the jth flexible load at the kth iteration, aijFor the elements of ith row and jth column of network topology adjacency matrix A, H*(k) T is an adjustment item of frequency modulation control and takes the value of 1 to n, omega is an adaptive global balance correction coefficient, and delta fi(k) Is the frequency offset value, f, at the kth iterationi(k) Frequency, f, measured for the kth iteration of a distributed renewable energy source equipped with a phase-locked loop*Is the nominal frequency of the system.
4. The cooperative control method for improving the stability of the new energy accessed to the weak grid system according to claim 1, wherein in the step C, if the active output power of each distributed renewable energy in the current step exceeds the maximum power limit, the distributed renewable energy operates according to the maximum constrained power, and the consistency state variable of the distributed renewable energy is updated; if the active output power of each distributed renewable energy source in the current step is smaller than the minimum power limit, the distributed renewable energy sources operate according to the minimum constraint power, and the consistency state variable of the distributed renewable energy sources is updated; and if grid connection or grid disconnection of the distributed renewable energy sources occurs, updating the network topological graph, recalculating the Laplace matrix L and the adjacency matrix A, and updating the consistency state variable.
5. The cooperative control method for improving the stability of the new energy access weak grid system according to claim 1, wherein in the step E, a specific method for adding frequency modulation control is as follows:
the additional frequency modulation control strategy is:
Figure FDA0003636416190000024
in the formula, delta f is the frequency deviation in the active power distribution network cluster, delta P is the sudden change of the required power of the flexible load, KsRegulating power, K, for a distributed renewable energy sourcedThe power is adjusted for the unit of flexible load.
6. The cooperative control method for improving the stability of the new energy access weak grid system according to claim 5, wherein in the step E, the calculation method of the adaptive frequency correction coefficient comprises the following steps:
step E1, when the frequency deviation is larger than the frequency deviation critical value, the power supply side and the load side participate in frequency modulation at the same time, and the calculation formula of the self-adaptive frequency correction coefficient is as follows:
Ω＝εi(Ks+Kd)
in the formula, KsRegulating power, K, for a unit of distributed renewable energydRegulating power, epsilon, for units of flexible loadiThe convergence coefficient of the ith distributed renewable energy source in the power distribution network.
And E2, when the frequency deviation is smaller than the frequency deviation critical value, the power supply side participates in frequency modulation independently, and the calculation formula of the self-adaptive frequency correction coefficient is as follows:
Ω＝εiKs
in the formula, KsRegulating power, epsilon, for a unit of distributed renewable energyiThe convergence coefficient of the ith distributed renewable energy source in the power distribution network.
7. The cooperative control method for improving the stability of the new energy access weak grid system according to claim 6, wherein the allowable range of the frequency deviation is [ -0.2Hz,0.2Hz ].
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